Predicting Neologisms for Marketing:A Text Mining Approach

International Journal of Economics and Management Studies

© 2020 by SSRG - IJEMS Journal

Volume 7 Issue 7

Year of Publication : 2020

Authors : Sang-Uk Jung, Jungho Byun, Seongyeol Bae, Donghwi Song

10.14445/23939125/IJEMS-V7I7P102

How to Cite?

Sang-Uk Jung, Jungho Byun, Seongyeol Bae, Donghwi Song, "Predicting Neologisms for Marketing:A Text Mining Approach," SSRG International Journal of Economics and Management Studies, vol. 7,  no. 7, pp. 5-9, 2020. Crossref, https://doi.org/10.14445/23939125/IJEMS-V7I7P102

Abstract:

An increasing number of companies rely on neologisms when implementing their marketing strategy. However, companies recognize that indiscriminate use of neologisms can haveabadimpactonmarketing, requiring them to evaluate the pros and cons of the neologism they apply. To help on these issues, this research focuses on creating a model predicting neologisms that are appropriate for marketing use. Using data collected with web-crawling from Korea’s largest community website, 415,000 terms for 6 forums are examined with network analysis, text mining, and logistic regression. We find that ‘Negative’, ‘Summary’, ‘Korean’ are the most meaningful variables when predicting appropriate neologisms for marketing use in Korea. Our model predicts that the ‘Ja-gang-du-chun’ will be a buzzword next year. Up-to-date results will come out with the updated and supplementary data sets. These findings suggest a way for the practitioner to predict a buzzword and how to use it in marketing.

Keywords:

Neologism, Marketing Intelligence, Online Community, Text Mining, Korean.

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